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在今天的企业环境如何使用机器学习

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首席架构师智库
发布2018-04-09 16:21:33
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发布2018-04-09 16:21:33
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文章被收录于专栏:超级架构师

One of the latest trends in the world of technology and engineering is “machine learning” — in fact, all of the big technology companies today have invested in artificial intelligence and machine learning projects.

The term “machine learning” was first defined by Arthur Samuel, way back in 1959. He defined it as “the ability to learn without being explicitly programmed,” which basically means that a machine could learn from its own mistakes and reprogram itself to improve its performance over time.

The idea gained popularity in the 90s when the concept of data mining came into existence. Data mining uses algorithms to look for patterns in a given set of information, which led to data-driven predictions and decision making. This encouraged engineers to develop complex machine learning algorithms by making use of data mining and predictive analytics.

Innovations that are driving business advantage

Today, machine learning algorithms are already being used widely in various ways. Here are some, everyday uses of machine learning that you probably didn’t know.

  1. The face detection feature in your phone camera is an example of what machine learning can do. Cameras can automatically click when someone smiles or take photos by simply blinking, looking at your phone. This is possible because of the advances in machine learning algorithms.
  2. The face recognition feature with which a computer can identify an individual from a photo is another use of machine learning. We use it often on Facebook, while automatically tagging friends in photos they appear.
  3. Have you ever noticed that your phone sometimes suggests freeing up space by deleting duplicate photos, photos containing the same image, which it automatically detect? This would not be possible without machine learning.
  4. Every time you search something on the Internet you make use of machine learning. Google uses machine learning to improve search results and search suggestions.
  5. Machine learning is used in anti-virus and anti-spam software to improve detection of malicious software, spyware, or adware on your devices.
  6. Machine learning is also changing the way vehicle systems are engineered and built. It is being used extensively in self-driving cars.

Machine learning becomes mainstream

The technology is advancing at a rapid pace as we continue to find new ways of using machine learning. Enterprises too, are keen to get a hold of machine learning for the betterment of future products and accomplishment of strategic goals.

Machine learning brings value to all the data that enterprises have been saving for years, by churning high volumes of data and helping gain deeper insights and improve decision-making. The figure below depicts some of the applications of machine learning across multiple industries.

Source: TCS

Future application to use machine learning

Machine learning algorithms are being used extensively to re-engineer business processes such as sales, marketing, logistics, procurement etc. across industries. The beauty of it all is that these algorithms keep getting better with time by itself.

The real reason behind this accelerated adoption of machine learning is that the algorithms are iterative in nature, repeatedly learning and probing to optimize outcomes. Every time an error is made, machine learning algorithms correct itself and begins another iteration of the analysis. And all of these calculations happen in milliseconds making it exceptionally efficient at optimizing decisions and predicting outcomes.

Machine learning makes it easier to devise sophisticated software systems without much human effort. Instead of spending years coding features or fine tuning a system with a lot of parameters, we can use machine learning to get done in a much shorter time span. Don’t be surprised if you soon begin to see and use technology and gadgets, which is as of now seen in science fiction movies.

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原始发表:2017-03-16,如有侵权请联系 cloudcommunity@tencent.com 删除

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目录
  • Innovations that are driving business advantage
  • Machine learning becomes mainstream
  • Future application to use machine learning
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